Defocus generation method for measuring the thickness of surface-hardened layers by a laser ultrasonic technique.

We developed a noncontact inspection method for measuring the thickness of surface-hardened layers using a laser ultrasonic technique in which a laser beam for generating ultrasonic surface waves was defocused on a specimen. Our method was based on the dependence of the ultrasonic surface-wave velocity on the thickness of the hardened layers. In the measurement, it is essential to generate a surface wave with a wavelength comparable to the hardened-layer thickness. It is known that the wavelength of the laser-generated surface wave depends on the beam diameter of the generation laser. We applied this control method of the wavelength of the surface wave (i.e., the defocus generation method) for measuring the hardened-layer thickness with higher accuracy and found that the results were in good agreement with the calculation.

Data Fusion of Multiview Ultrasonic Imaging for Characterization of Large Defects.

The multiview total focusing method (TFM) enables a region of interest within a specimen to be imaged using different ray paths and wave-mode combinations. For defects larger than the ultrasonic wavelength, different portions of the same defect may manifest in a number of views. For a crack, the tip diffraction response may be evident in certain views and the specular reflection in others. Accurate characterization of large defects requires the information in multiple views to be combined. In this work, three data fusion methodologies are presented: a simple sum over all views, a sum weighted according to the inverse of the noise in each view, and a matched filter approach. Four large defects are examined; one stress corrosion crack (SCC), two weld cracks, and a pair of slagline defects in a weld. The matched filter (matched to a small circular void) provided significant improvement over the best individual view. The data fusion process incorporates artifact removal, where nondefect artifact signals within each image view are identified and masked, using a single defect-free data set for training. The matched filter was able to accurately visualize the full 3-D extent of the four defects, allowing characterization via the decibel drop method. When compared to X-ray computed tomography and micrograph data in the case of the SCC, the matched filter fusion provided excellent agreement. Its performance was also superior to any individual view while providing a single fused image that is easier for an operator to interpret than a set of multiview images.